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Introduction Most gay, bisexual and other men who have sex with men (GBMSM) live in rights‐constrained environments making retaining them in research to be as hard as recruiting them. To evaluate Anza Mapema, an HIV risk‐reduction programme in Kisumu, Kenya, we examined the enrolment sociodemographic, behavioural, psychosocial and clinical factors associated with missing two or more follow‐up visits for GBMSM participating in Anza Mapema. Methods Between August 2015 and November 2017, GBMSM were enrolled and followed in a prospective cohort study with quarterly visits over 12 months. At enrolment, men were tested for HIV and sexually transmitted infections and completed questionnaires via audio computer‐assisted self‐interview. Because the Kenya Ministry of Health recommends HIV testing every three to six months for GBMSM, the retention outcome in this cross sectional analysis was defined as missing two consecutive follow‐up visits (vs. not missing two or more consecutive visits). Multivariable logistic regression estimated the adjusted odds ratios (aOR) and 95% confidence intervals (CI) for the associations of the enrolment characteristics with the binary outcome of retention. Results and discussion Among 609 enrolled HIV‐negative GBMSM, the median age was 23 years (interquartile range, 21 to 28 years), 19.0% had completed ≤8 years of education and 4.1% had resided in the study area <1 year at enrolment. After enrolment, 19.7% missed two consecutive follow‐up visits. In the final multivariable model, the odds of missing two consecutive follow‐up visits were higher for men who: resided in the study area <1 year at enrolment (aOR, 4.14; 95% CI: 1.77 to 9.68), were not living with a male sexual partner (aOR, 1.59; 95% CI: 1.01 to 2.50), and engaged in transactional sex during the last three months (aOR, 1.70; 95% CI: 1.08 to 2.67). Conclusions One in five men missed two consecutive follow‐up visits during this HIV prevention study despite intensive retention efforts and compensation for travel and participation. Participants with recent community arrival may require special support to optimize their retention in HIV prevention activities. Live‐in partners of participants may be enlisted to support greater engagement in prevention programmes, and men who engage in transactional sex will need enhanced counselling and support to stay in longitudinal studies.

Despite the availability of effective medication, blood pressure control rates are low, particularly in low‐ and middle‐income countries. Adherence to medication and follow‐up visits are important factors in blood pressure control. This study assessed the effectiveness of reminder telephone calls on follow‐up visits and blood pressure control among hypertensive patients as part of the Mumbai Hypertension Project. This project was initiated by PATH with the support from Resolve to Save Lives from January 2019 to February 2020. The study included hypertensive patients attending 164 private practices in Mumbai, India; practitioners screened all adults visiting their clinic during the project period. Among 13 184 hypertensive patients registered, the mean age was 53 years (SD = 12.38) and 52% were female. Among the 11 544 patients that provided phone numbers and gave consent for follow‐up calls, 9528 responded to phone calls at least once and 5250 patients followed up at least once. Of the 5250 patients, 82% visited the clinic for follow‐up visit within one month after receiving the phone call. The blood pressure control rate among those who answered phone calls and who did not answer phone calls increased from 23.6% to 48.8% (P <.001) and 21.0% to 44.3% (P <.001), respectively. The blood pressure control rate at follow‐up was significantly associated with phone calls (OR: 1.51, 95% CI: 1.34 ‐ 1.71). The study demonstrates that telephone call intervention and follow‐up visits can improve patient retention in care and, subsequently, blood pressure control among hypertensive patients attending urban private sector clinics in India.

Background Telehealth rapidly expanded since the outbreak of the COVID-19 pandemic. This study aims to understand how telehealth can substitute in-person services by 1) estimating the changes in non-COVID emergency department (ED) visits, hospitalizations, and care costs among US Medicare beneficiaries by visit modality (telehealth vs. in-person) during the COVID-19 pandemic relative to the previous year; 2) comparing the follow-up time and patterns between telehealth and in-person care. Methods A retrospective and longitudinal study design using US Medicare patients 65 years or older from an Accountable Care Organization (ACO). The study period was April-December 2020, and the baseline period was March 2019 – February 2020. The sample included 16,222 patients, 338,872 patient-month records and 134,375 outpatient encounters. Patients were categorized as non-users, telehealth only, in-person care only and users of both types. Outcomes included the number of unplanned events and costs per month at the patient level; number of days until the next visit and whether the next visit happened within 3-, 7-, 14- and 30-days at the encounter level. All analyses were adjusted for patient characteristics and seasonal trends. Results Beneficiaries who used only telehealth or in-person care had comparable baseline health conditions but were healthier than those who used both types of services. During the study period, the telehealth only group had significantly fewer ED visits/hospitalizations and lower Medicare payments than the baseline (ED 13.2, 95% CI [11.6, 14.7] vs. 24.6 per 1,000 patients per month and hospitalization 8.1 [6.7, 9.4] vs. 12.7); the in-person only group had significantly fewer ED visits (21.9 [20.3, 23.5] vs. 26.1) and lower Medicare payments, but not hospitalizations; the both-types group had significantly more hospitalizations (23.0 [21.4, 24.6] vs. 17.8). Telehealth was not significantly different from in-person encounters in number of days until the next visit (33.4 vs. 31.2 days) or the probabilities of 3- and 7-day follow-up visits (9.2 vs. 9.3% and 21.8 vs.23.5%). Conclusions Patients and providers treated telehealth and in-person visits as substitutes and used either depending on medical needs and availability. Telehealth did not lead to sooner or more follow-up visits than in-person services.

Introduction The provision of voluntary medical male circumcision (VMMC) services was piloted in three public sector facilities in a high HIV disease burden, low circumcision rate province in South Africa to inform policy and operational guidance for scale‐up of the service for HIV prevention. We report on adverse events (AEs) experienced by clients following the circumcision procedure. Methods Prospective recruitment of HIV‐negative males aged 12 and older volunteering to be circumcised at three select public health facilities in KwaZulu‐Natal between November 2010 and May 2011. Volunteers underwent standardized medical screening including a physical assessment prior to the surgical procedure being performed. AEs were monitored at three time intervals over a 21‐day period post‐operatively to determine safety outcomes in this pilot demonstration programme. Results A total of 602 volunteers participated in this study. The median age of the volunteers was 22 years (range 12–56). Most participants (75.6%) returned for the 48‐hour post‐operative visit; 51.0% for day seven visit and 26.1% for the 21st day visit. Participants aged 20–24 were most likely to return. The AE rate was 0.2% intra‐operatively. The frequency of moderate AEs was 0.7, 0.3 and 0.6% at 2‐, 7‐ and 21‐day visits, respectively. The frequency of severe AEs was 0.4, 0.3 and 0.6% at 2‐, 7‐ and 21‐day visits, respectively. Swelling and wound infection were the most common AEs with mean appearance duration of seven days. Clients aged between 35 and 56 years presented with most AEs (3.0%). Conclusions VMMC can be delivered safely at resource‐limited settings. The intensive three‐visit post‐operative review practice may be unfeasible due to high attrition rates over time, particularly amongst older men.

PurposeTo understand the role of routine follow-up visits in addressing prostate cancer survivors’ supportive care and information needs.MethodsWe audio-recorded follow-up visits of 32 prostate cancer survivors. Follow-up visits were analyzed according to the Verona Network of Sequence Analysis. We categorized survivors’ cues, concerns, and questions into five supportive care domains and divided the responses by the healthcare professionals into providing versus reducing space that is to determine whether or not the response invites the patient to talk more about the expressed cue or concern.ResultsProstate cancer survivors mostly expressed cues, concerns, and questions (in the health system and information domain) about test results, potential impotence treatment, follow-up appointments, and (their) cancer treatment during follow-up visits. Survivors also expressed urinary complaints (physical and daily living domain) and worry about the recurrence of prostate cancer (psychological domain). Healthcare professionals were two times more likely to provide space on cues and concerns related to the physical and daily living domain than to psychological related issues.ConclusionFollow-up visits can serve to address prostate cancer survivors’ supportive care and information needs, especially on the health system, information, and physical and daily living domain. Survivors also expressed problems in the psychological domain, although healthcare professionals scarcely provided space to these issues. We would like to encourage clinicians to use these results to personalize follow-up care. Also, these data can be used to develop tailored (eHealth) interventions to address supportive care and information needs and to develop new models of survivorship care delivery.

With the widespread implementation of automated hematology systems, Reflex testing plays a critical role in result verification. However, overly sensitive Reflex rules may lead to excessive repeat testing, increasing workload and prolonging sample turnaround time. This study optimized Reflex rules to improve workflow efficiency while maintaining analytical safety and accuracy. A retrospective analysis was performed on 78,364 CBC results generated by the Sysmex XN-9100 hematology automation line in June 2025, including 43,758 outpatient and 34,606 emergency/ward samples. Reflex rules involving LW, PLT-F, WPC, and RET channels were optimized by differentiating initial and follow-up visit samples, introducing a 7-day historical result fluctuation safety range, and simplifying IP message combinations. Middleware simulation compared total Reflex rates and special-channel repeat counts before and after optimization. Existing autoverification logic, critical alert rules, manual review workflow, and high-risk disease-related repeat testing rules were retained. After optimization, total Reflex rates decreased significantly in both work areas (p < 0.01), from 16.03% to 14.36% in the outpatient area (relative reduction, 10.43%) and from 24.38% to 15.00% in the emergency/ward area (relative reduction, 38.47%). In the emergency/ward area, PLT-F, WPC, and RET repeat counts decreased by 44.86%, 49.19%, and 61.89%, respectively. XN automation line Reflex rule optimization reduced unnecessary repeat testing through initial/follow-up visit differentiation and historical fluctuation thresholds while retaining core risk-interception rules, supporting improved hematology workflow efficiency and reduced reagent consumption.

Abstract Rationale Various causes can contribute to the high rates of readmission among patients hospitalized with chronic obstructive pulmonary disease (COPD). Objectives To determine the frequency and predictors of early readmission among patients aged 40–64 years, hospitalized with COPD. Methods In a retrospective cohort study, using a large national commercial insurance database, we obtained the clinical information within 12 months of the index hospitalization and 30 days after discharge. Measurements and Main Results Primary outcome was early readmission, defined as hospitalization within 30 days of discharge. We categorized predictor variables as patient, provider, and system factors, and compared these variables between patients readmitted and those not readmitted. Logistic regression was used for multivariable analysis. Of 8,263 patients who met the inclusion criteria, 741 (8.9%) had early readmission. Multivariable analysis showed patient factors (male, history of heart failure, lung cancer, osteoporosis, and depression), provider factors (no prior prescription of statin within 12 mo of the index hospitalization and no prescription of short-acting bronchodilator, oral steroid and antibiotic on discharge), and system factors (length of stay, <2 or >5 d and lack of follow-up visit after discharge) were associated with early readmission among patients hospitalized with COPD. The C-statistic of the model including patient characteristics was 0.677 (95% confidence interval, 0.656–0.697), which was improved to 0.717 (95% confidence interval, 0.702–0.732) after addition of provider- and system-based factors. Conclusions One of 11 patients hospitalized with COPD is readmitted within 30 days of discharge. Provider and system factors are important modifiable risk factors of early readmission.

While guidelines recommend follow-up visits after an acute exacerbation of COPD (AECOPD), the optimal healthcare facility, timing and its effect on long-term mortality are not well known. In this retrospective case-control study, Finnish nationwide healthcare and mortality registries were linked to determine the association of a follow-up visit in secondary or primary care within 3 and 6 months after severe AECOPD on 2-year mortality. A conditional fixed-effects logistic regression analysis with 23 covariates was used. A nested case-control study design was applied with matching for age, sex, and multimorbidity in a 1:4 ratio. A time-varying Cox sensitivity analysis was performed to test result robustness. In 2018, the Finnish prevalent COPD population consisted of 63 442 patients, of whom 10% experienced an AECOPD. After the AECOPD, 23% of the patients had a follow-up visit within 3 months. A follow-up in primary care wasn't associated with mortality (OR 1.06, 95% CI 0.90-1.24). However, patients with a follow-up in secondary care were at an increased mortality risk compared with controls without a follow-up (OR 1.62, 95% CI 1.37-1.92). In sensitivity analysis the effect lost statistical significance (HR 1.05, 95% CI 0.35-3.12) but a secondary care follow-up with an add-on primary care follow-up was associated with lower mortality (HR 0.56, 95% CI 0.51-0.61). The strongest predisposing factors were older age, comorbidities such as lung cancer, heart failure and atherosclerosis obliterans, home care, readmission, length of inpatient stay and prior health care use burden. By extending the follow-up time window to 6 months, the results remained largely similar. While we were able to quantify the effect of several patient characteristics on 2-year mortality after AECOPD, the effect of follow-up visits was unclear, likely due to residual confounding by indication. Further studies with even more robust methodology are needed.

Background Following the first report of the COVID-19 case in Ethiopia on March 13, 2020, the country promptly adopted a lockdown policy to contain the virus’s spread. Responding to the healthcare burden imposed by the COVID-19 pandemic had to be coupled with ensuring essential health care services. This study assessed the impact of COVID-19 on the trends in hospital visits and admissions at Tikur Anbessa Specialized Hospital by comparing the rate of follow-up clinic visits and admissions for the 3 months before and after the first report of the COVID-19 case. Methods A retrospective, time-series study examined the trend in follow-up visits and admissions between December 11, 2019, to June 7, 2020, with the 1st case of the COVID-19 report in Ethiopia (March 13, 2020) as a reference time. To control seasonal effects and random fluctuation, we have compared health care utilization to its equivalent period in 2018/19. A data extraction tool was used to collect secondary data from each unit’s electronic medical recordings and logbooks. Results A total of 7717 visits from eight follow-up clinics and 3310 admissions were collected 3 months before the onset of COVID-19. During the following 3 months after the onset of the pandemic, 4597 visits and 2383 admissions were collected. Overall, a 40.4% decrease in follow-up visits and a 28% decline in admissions were observed during the COVID-19 pandemic. A drop in the daily follow-up visits was observed for both genders. The number of visits in all follow-up clinics in 2019/2020 decreased compared to the same months in 2018/19 ( p  < 0.05). Follow-up visits were substantially lower for renal patients (− 68%), patients with neurologic problems (− 53.9%), antiretroviral treatment clinics (− 52.3%), cardiac patients (− 51.4%). Although pediatric emergency admission was significantly lower (− 54.1%) from the baseline ( p  = 0.04), admissions from the general pediatric and adult wards did not show a significant difference. Conclusions A decline in follow-up clinic visits and emergency admissions was observed during the first months of the COVID-19 pandemic. This will increase the possibility of avoidable morbidity and mortality due to non-COVID-19-related illnesses. Further studies are needed to explore the reasons for the decline and track the pandemic’s long-term effects among non-COVID-19 patients.

The predator-prey shell game predicts random movement of prey across the landscape, whereas the behavioral response race and landscape of fear models predict that there should be a negative relationship between the spatial distribution of a predator and its behaviorally active prey. Additionally, prey have imperfect information on the whereabouts of their predator, which the predator should incorporate in its patch use strategy. I used a one-predator-one-prey system, puma ( Puma concolor )-mule deer ( Odocoileus hemionus ) to test the following predictions regarding predator-prey distribution and patch use by the predator. (1) Pumas will spend more time in high prey risk/low prey use habitat types, while deer will spend their time in low-risk habitats. Pumas should (2) select large forage patches more often, (3) remain in large patches longer, and (4) revisit individual large patches more often than individual smaller ones. I tested these predictions with an extensive telemetry data set collected over 16 years in a study area of patchy forested habitat. When active, pumas spent significantly less time in open areas of low intrinsic predation risk than did deer. Pumas used large patches more than expected, revisited individual large patches significantly more often than smaller ones, and stayed significantly longer in larger patches than in smaller ones. The results supported the prediction of a negative relationship in the spatial distribution of a predator and its prey and indicated that the predator is incorporating the prey's imperfect information about its presence. These results indicate a behavioral complexity on the landscape scale that can have far-reaching impacts on predator-prey interactions.